Speaker labeled background data is an essential requirement for most state-of-the-art
approaches in speaker recognition, eg, xvectors and i-vector/PLDA. However, in reality it is …

Probabilistic Linear Discriminant Analysis (PLDA) is the most efficient backend for i-vectors.
However, it requires labeled background data which can be difficult to access in practice …

Recent advances in Deep Learning (DL) for speaker recognition have improved the
performance but are constrained to the need of labels for the background data, which is …

In speaker recognition, i-vectors have been the state-of-the-art unsupervised technique over
the last few years, whereas x-vectors is becoming the state-of-the-art supervised technique …